1. Approach : Sift through the data by checking NaNs,
getting summary statistics, and since this is a time series data, plot
time series trends. From the time series trends, I noticed some ups and
downs in variables like bat speed, hand speed, etc. which can be
attributed to noise while collecting the data. I used a low-pass
butterworth filter having a cutoff of 25Hz for the metrics in the time
series plots and 10 Hz for barrel & knob tracking data.
After that I focused on dividing the visuals into two parts with the
swing views from three different perspectives and time series plots of
the metrics. I also added a 3D figure to properly visualize the swing
path.
2. Observation : Considering similar pitch conditions
for both the players, I came up with the following observations.
Player 1 has a gradual downward swing that transitions into a steep upward motion, indicating a focus on producing lift, with relatively controlled body rotation and an elevated vertical bat angle to maximize fly ball potential. Their extended bat path post-contact, though slightly slower in achieving the same level of bat speed, is characterized by a controlled swing. This could result into swings with higher launch angles and better adjustability to pitches in different locations.
Player 2 shows an aggressive swing that levels off near contact with a compact follow-through (from 3D Viz), achieving higher bat speed but also a flattened bat path, indicating a more explosive swing focused on power with potentially a line-drive approach. This aggressive approach might help with high exit velocity, but it might also result into ground outs due to the bat path.
3. Extension :